Structural response reconstruction based on moving window Kalman filtering algorithm

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Journal of Vibration and Shock ›› 2021, Vol. 40 ›› Issue (21) : 90-96.

ZHANG Xiaohua, WU Zhibiao, WU Shengbin, HUANG Meiping

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Abstract

The classical Kalman filter (KF) algorithm is a powerful tool to reconstruct the unmeasured responses but needing available process and measurement noise covariance and always assuming to be constants. However, it is generally difficult to determine in advance the noise covariance and they are time-varied. This paper thus investigates responses reconstruction by using the moving-window Kalman filter (MWKF) with unknown measurement and process noise covariance. The measurement and process noise covariance was firstly evaluated by utilizing the moving-window estimation technique and measurements. Then the structural responses at unmeasured locations were reconstructed based on KF algorithm with limited measurements. Numerical and experimental investigations were conducted by using a three-storey frame structure to verify the effectiveness and feasibility of the MWKF in response reconstruction. The results indicate that the measurement and process noise covariance can be well estimated and the reconstructed responses agree well with the real or measured responses.

Key words

unknown noise variance / Kalman filer / moving-window / limited measurements / response reconstruction

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ZHANG Xiaohua, WU Zhibiao, WU Shengbin, HUANG Meiping. Structural response reconstruction based on moving window Kalman filtering algorithm[J]. Journal of Vibration and Shock, 2021, 40(21): 90-96

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